mradermacher/code-llama-3-8b-i1-gguf overview

{
  "metadata": {},
  "card_data": {
    "base_model": "ajibawa-2023/Code-Llama-3-8B",
    "datasets": [
      "ajibawa-2023/Code-290k-ShareGPT",
      "m-a-p/CodeFeedback-Filtered-Instruction",
      "m-a-p/Code-Feedback",
      "microsoft/orca-math-word-problems-200k"
    ],
    "language": [
      "en"
    ],
    "library_name": "transformers",
    "license": "llama3",
    "quantized_by": "mradermacher",
    "tags": [
      "code",
      "Python",
      "Cpp",
      "PHP",
      "JS",
      "Java",
      "Rust",
      "Ruby",
      "SQL",
      "MySql",
      "R",
      "Julia"
    ],
    "frontmatter": {
      "base_model": "ajibawa-2023/Code-Llama-3-8B",
      "datasets": [
        "ajibawa-2023/Code-290k-ShareGPT",
        "m-a-p/CodeFeedback-Filtered-Instruction",
        "m-a-p/Code-Feedback",
        "microsoft/orca-math-word-problems-200k"
      ],
      "language": [
        "en"
      ],
      "library_name": "transformers",
      "license": "llama3",
      "quantized_by": "mradermacher",
      "tags": [
        "code",
        "Python",
        "Cpp",
        "PHP",
        "JS",
        "Java",
        "Rust",
        "Ruby",
        "SQL",
        "MySql",
        "R",
        "Julia"
      ]
    },
    "hero_image_url": "https://www.nethype.de/huggingface_embed/quantpplgraph.png",
    "summary": "## About     weighted/imatrix quants of https://huggingface.co/ajibawa-2023/Code-Llama-3-8B  static quants are available at https://huggingface.co/mradermacher/Code-Llama-3-8B-GGUF",
    "quick_links": [],
    "benchmark_table_html": "",
    "readme_markdown": "---\nbase_model: ajibawa-2023/Code-Llama-3-8B\ndatasets:\n- ajibawa-2023/Code-290k-ShareGPT\n- m-a-p/CodeFeedback-Filtered-Instruction\n- m-a-p/Code-Feedback\n- microsoft/orca-math-word-problems-200k\nlanguage:\n- en\nlibrary_name: transformers\nlicense: llama3\nquantized_by: mradermacher\ntags:\n- code\n- Python\n- Cpp\n- PHP\n- JS\n- Java\n- Rust\n- Ruby\n- SQL\n- MySql\n- R\n- Julia\n---\n## About\n\n<!-- ### quantize_version: 2 -->\n<!-- ### output_tensor_quantised: 1 -->\n<!-- ### convert_type: hf -->\n<!-- ### vocab_type:  -->\nweighted/imatrix quants of https://huggingface.co/ajibawa-2023/Code-Llama-3-8B\n\n<!-- provided-files -->\nstatic quants are available at https://huggingface.co/mradermacher/Code-Llama-3-8B-GGUF\n## Usage\n\nIf you are unsure how to use GGUF files, refer to one of [TheBloke's\nREADMEs](https://huggingface.co/TheBloke/KafkaLM-70B-German-V0.1-GGUF) for\nmore details, including on how to concatenate multi-part files.\n\n## Provided Quants\n\n(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)\n\n| Link | Type | Size/GB | Notes |\n|:-----|:-----|--------:|:------|\n| [GGUF](https://huggingface.co/mradermacher/Code-Llama-3-8B-i1-GGUF/resolve/main/Code-Llama-3-8B.i1-IQ1_S.gguf) | i1-IQ1_S | 2.1 | for the desperate |\n| [GGUF](https://huggingface.co/mradermacher/Code-Llama-3-8B-i1-GGUF/resolve/main/Code-Llama-3-8B.i1-IQ1_M.gguf) | i1-IQ1_M | 2.3 | mostly desperate |\n| [GGUF](https://huggingface.co/mradermacher/Code-Llama-3-8B-i1-GGUF/resolve/main/Code-Llama-3-8B.i1-IQ2_XXS.gguf) | i1-IQ2_XXS | 2.5 |  |\n| [GGUF](https://huggingface.co/mradermacher/Code-Llama-3-8B-i1-GGUF/resolve/main/Code-Llama-3-8B.i1-IQ2_XS.gguf) | i1-IQ2_XS | 2.7 |  |\n| [GGUF](https://huggingface.co/mradermacher/Code-Llama-3-8B-i1-GGUF/resolve/main/Code-Llama-3-8B.i1-IQ2_S.gguf) | i1-IQ2_S | 2.9 |  |\n| [GGUF](https://huggingface.co/mradermacher/Code-Llama-3-8B-i1-GGUF/resolve/main/Code-Llama-3-8B.i1-IQ2_M.gguf) | i1-IQ2_M | 3.0 |  |\n| [GGUF](https://huggingface.co/mradermacher/Code-Llama-3-8B-i1-GGUF/resolve/main/Code-Llama-3-8B.i1-Q2_K.gguf) | i1-Q2_K | 3.3 | IQ3_XXS probably better |\n| [GGUF](https://huggingface.co/mradermacher/Code-Llama-3-8B-i1-GGUF/resolve/main/Code-Llama-3-8B.i1-IQ3_XXS.gguf) | i1-IQ3_XXS | 3.4 | lower quality |\n| [GGUF](https://huggingface.co/mradermacher/Code-Llama-3-8B-i1-GGUF/resolve/main/Code-Llama-3-8B.i1-IQ3_XS.gguf) | i1-IQ3_XS | 3.6 |  |\n| [GGUF](https://huggingface.co/mradermacher/Code-Llama-3-8B-i1-GGUF/resolve/main/Code-Llama-3-8B.i1-Q3_K_S.gguf) | i1-Q3_K_S | 3.8 | IQ3_XS probably better |\n| [GGUF](https://huggingface.co/mradermacher/Code-Llama-3-8B-i1-GGUF/resolve/main/Code-Llama-3-8B.i1-IQ3_S.gguf) | i1-IQ3_S | 3.8 | beats Q3_K* |\n| [GGUF](https://huggingface.co/mradermacher/Code-Llama-3-8B-i1-GGUF/resolve/main/Code-Llama-3-8B.i1-IQ3_M.gguf) | i1-IQ3_M | 3.9 |  |\n| [GGUF](https://huggingface.co/mradermacher/Code-Llama-3-8B-i1-GGUF/resolve/main/Code-Llama-3-8B.i1-Q3_K_M.gguf) | i1-Q3_K_M | 4.1 | IQ3_S probably better |\n| [GGUF](https://huggingface.co/mradermacher/Code-Llama-3-8B-i1-GGUF/resolve/main/Code-Llama-3-8B.i1-Q3_K_L.gguf) | i1-Q3_K_L | 4.4 | IQ3_M probably better |\n| [GGUF](https://huggingface.co/mradermacher/Code-Llama-3-8B-i1-GGUF/resolve/main/Code-Llama-3-8B.i1-IQ4_XS.gguf) | i1-IQ4_XS | 4.5 |  |\n| [GGUF](https://huggingface.co/mradermacher/Code-Llama-3-8B-i1-GGUF/resolve/main/Code-Llama-3-8B.i1-Q4_0.gguf) | i1-Q4_0 | 4.8 | fast, low quality |\n| [GGUF](https://huggingface.co/mradermacher/Code-Llama-3-8B-i1-GGUF/resolve/main/Code-Llama-3-8B.i1-Q4_K_S.gguf) | i1-Q4_K_S | 4.8 | optimal size/speed/quality |\n| [GGUF](https://huggingface.co/mradermacher/Code-Llama-3-8B-i1-GGUF/resolve/main/Code-Llama-3-8B.i1-Q4_K_M.gguf) | i1-Q4_K_M | 5.0 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/Code-Llama-3-8B-i1-GGUF/resolve/main/Code-Llama-3-8B.i1-Q5_K_S.gguf) | i1-Q5_K_S | 5.7 |  |\n| [GGUF](https://huggingface.co/mradermacher/Code-Llama-3-8B-i1-GGUF/resolve/main/Code-Llama-3-8B.i1-Q5_K_M.gguf) | i1-Q5_K_M | 5.8 |  |\n| [GGUF](https://huggingface.co/mradermacher/Code-Llama-3-8B-i1-GGUF/resolve/main/Code-Llama-3-8B.i1-Q6_K.gguf) | i1-Q6_K | 6.7 | practically like static Q6_K |\n\nHere is a handy graph by ikawrakow comparing some lower-quality quant\ntypes (lower is better):\n\n![image.png](https://www.nethype.de/huggingface_embed/quantpplgraph.png)\n\nAnd here are Artefact2's thoughts on the matter:\nhttps://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9\n\n## FAQ / Model Request\n\nSee https://huggingface.co/mradermacher/model_requests for some answers to\nquestions you might have and/or if you want some other model quantized.\n\n## Thanks\n\nI thank my company, [nethype GmbH](https://www.nethype.de/), for letting\nme use its servers and providing upgrades to my workstation to enable\nthis work in my free time.\n\n<!-- end -->\n",
    "related_quantizations": []
  },
  "tags": [
    "transformers",
    "gguf",
    "code",
    "Python",
    "Cpp",
    "PHP",
    "JS",
    "Java",
    "Rust",
    "Ruby",
    "SQL",
    "MySql",
    "R",
    "Julia",
    "en",
    "dataset:ajibawa-2023/Code-290k-ShareGPT",
    "dataset:m-a-p/CodeFeedback-Filtered-Instruction",
    "dataset:m-a-p/Code-Feedback",
    "dataset:microsoft/orca-math-word-problems-200k",
    "base_model:ajibawa-2023/Code-Llama-3-8B",
    "base_model:quantized:ajibawa-2023/Code-Llama-3-8B",
    "license:llama3",
    "endpoints_compatible",
    "region:us",
    "imatrix",
    "conversational"
  ],
  "likes": 1,
  "downloads": 133,
  "gated": false,
  "private": false,
  "last_modified": "2024-05-08T04:18:18.000Z",
  "created_at": "2024-05-07T15:27:14.000Z",
  "pipeline_tag": "",
  "library_name": "transformers"
}

{
  "_id": "663a48529613725d94dd6473",
  "id": "mradermacher/Code-Llama-3-8B-i1-GGUF",
  "modelId": "mradermacher/Code-Llama-3-8B-i1-GGUF",
  "sha": "fb46c984c61f583ddcd287e4b090770af35d95ee",
  "createdAt": "2024-05-07T15:27:14.000Z",
  "lastModified": "2024-05-08T04:18:18.000Z",
  "author": "mradermacher",
  "downloads": 133,
  "likes": 1,
  "gated": false,
  "private": false,
  "pipeline_tag": "",
  "library_name": "transformers",
  "siblings_count": 24
}